ID 原文 译文
9764 针对MCPC雷达信号常规脉冲压缩易产生高距离旁瓣而导致强目标邻近的弱小目标检测困难问题,通过对MCPC雷达信号进行建模分析并结合其信号特点,提出了一种MCPC雷达信号自适应脉冲压缩算法。 Aimed at MCPC regular pulse compression radar signal is easy to produce high range sidelobe and cause strong target neighbouring weak target detection, a difficult problem of MCPC radar signal modeling analysis and combining with the characteristics of the signal, puts forward a kind of MCPC radar signal adaptive pulse compression algorithm.
9765 通过利用循环迭代获取每个距离单元的最优匹配滤波器,从而有效抑制了距离旁瓣,提高了对邻近距离单元弱小目标的检测能力。 Through the use of loop iteration to obtain the optimal matched filter per unit of distance, thus effectively suppresses the range sidelobe, increase the distance of adjacent unit weak target detection ability.
9766 仿真实验验证了该方法的有效性,并进一步分析了编码方式对脉冲压缩距离旁瓣的影响。 Simulation results verify the effectiveness of the proposed method, and further analyzes the encoding of the influence of pulse compression distance sidelobe.
9767 基于最大非圆率非圆信号特点,提出一种实值张量旋转不变子空间(estimation signal parameters via rotational invariance techniques,ESPRIT)算法。 Based on the maximum rate of non-circular non-circular signal characteristic, proposed one kind of real value tensor rotation invariant subspace (estimation signal parameters via rotational invariance techniques, ESPRIT) algorithm.
9768 首先,通过研究张量与矩阵之间的转化关系,将阵列接收数据矩阵推广到张量空间; ‭First, through studying the relation between tensor and matrix transformation, the array to receive data matrix tensor space;
9769 然后,利用欧拉公式将阵列接收数据张量转化成余弦与正弦数据张量,根据阵列维数将其分别在各维上加以拼接,并对拼接的实值数据张量做高阶奇异值分解,获取信号子空间; Then, by using euler's formula will receive data array tensor into cosine and sine tensor data, according to the array dimensions on it in each dimension respectively splicing, and splicing the real value of data tensor do higher order singular value decomposition, to obtain the signal subspace;
9770 最后,通过构造选择矩阵和进行特征分解,来联合估计阵列各维相位差,实现波达方向估计。 Finally, through the selection of structure matrix decomposition and characteristics, to jointly estimate the dimensional array phase difference, the realization of doa estimation. ‭
9771 实验仿真结果表明,此算法具有良好的分辨力和测角精度。 The experimental simulation results show that this algorithm has good resolution and accuracy of Angle measuring.
9772 针对杂波环境下多传感器跟踪多目标的问题,提出了一种基于速度方位约束的多传感器模糊数据互联算法(multi-sensor fuzzy data association method based on velocity and azimuth,VA-MSFDA)。 For clutter environment multi-sensor multi-target tracking problem, this paper proposes a multi-sensor fuzzy data interconnection based on velocity azimuth constraint algorithm (multi - sensor fuzzy data association method -based on velocity and azimuth, VA - MSFDA).
9773 该算法首先利用方位速度信息对确认区域内的有效量测作进一步筛选,剔除部分虚假量测,然后基于模糊聚类方法计算候选量测与观测区域内各目标互联的概率,应用顺序结构多传感器联合概率数据互联(multi-sensor joint probabilistic data association algorithm,MSJPDA)原理,依次处理各传感器中的目标测量数据,实现对多目标的跟踪。 The algorithm firstly using azimuth velocity information to confirm the area of effective measure for further screening, eliminate some false measurement, and then based on the fuzzy clustering method to calculate the candidate area measurement and observation probability of each target interconnected application order structure of multi-sensor data association (multi - sensor to be probabilistic data association algorithm, MSJPDA) principle, the processing of the target of each sensor measurement data in turn, the implementation of multiple target tracking.